@inproceedings{Grum2022,
  author    = {Grum, Marcus},
  title     = {Context-aware, intelligent musical instruments for improving knowledge-intensive business processes},
  series = {Business modeling and software design},
  volume    = {453},
  booktitle = {Business modeling and software design},
  editor    = {Shishkov, Boris},
  publisher = {Springer},
  address   = {Cham},
  isbn      = {978-3-031-11509-7},
  doi       = {10.1007/978-3-031-11510-3_5},
  pages     = {69 -- 88},
  year      = {2022},
  abstract  = {With shorter song publication cycles in music industries and a reduced number of physical contact opportunities because of disruptions that may be an obstacle for musicians to cooperate, collaborative time consumption is a highly relevant target factor providing a chance for feedback in contemporary music production processes. This work aims to extend prior research on knowledge transfer velocity by augmenting traditional designs of musical instruments with (I) Digital Twins, (II) Internet of Things and (III) Cyber-Physical System capabilities and consider a new type of musical instrument as a tool to improve knowledge transfers at knowledge-intensive forms of business processes. In a design-science-oriented way, a prototype of a sensitive guitar is constructed as information and cyber-physical system. Findings show that this intelligent SensGuitar increases feedback opportunities. This study establishes the importance of conversion-specific music production processes and novel forms of interactions at guitar playing as drivers of high knowledge transfer velocities in teams and among individuals.},
  language  = {en}
}
@inproceedings{VladovaUllrichSultanowetal.2023,
  author    = {Vladova, Gergana and Ullrich, Andr{\´e} and Sultanow, Eldar and Tobolla, Marinho and Sebrak, Sebastian and Czarnecki, Christian and Brockmann, Carsten},
  title     = {Visual analytics for knowledge management},
  series = {Informatik 2023},
  booktitle = {Informatik 2023},
  editor    = {Klein, Maike and Krupka, Daniel and Winter, Cornelia and Wohlgemuth, Volker},
  publisher = {Gesellschaft f{\"u}r Informatik e.V. (GI)},
  address   = {Bonn},
  isbn      = {978-3-88579-731-9},
  issn      = {1617-5468},
  doi       = {10.18420/inf2023_187},
  pages     = {1851 -- 1870},
  year      = {2023},
  abstract  = {The management of knowledge in organizations considers both established long-term processes and cooperation in agile project teams. Since knowledge can be both tacit and explicit, its transfer from the individual to the organizational knowledge base poses a challenge in organizations. This challenge increases when the fluctuation of knowledge carriers is exceptionally high. Especially in large projects in which external consultants are involved, there is a risk that critical, company-relevant knowledge generated in the project will leave the company with the external knowledge carrier and thus be lost. In this paper, we show the advantages of an early warning system for knowledge management to avoid this loss. In particular, the potential of visual analytics in the context of knowledge management systems is presented and discussed. We present a project for the development of a business-critical software system and discuss the first implementations and results.},
  language  = {en}
}